Indicators for smart cities: tax illicit analysis through data mining
The anomalies in the data coexist in the databases and in the non-traditional data that can be accessed and produced by a tax administration, whether these data are of internal or external origin. The analysis of certain anomalies in the data could lead to the discovery of patterns that respond to d...
- Autores:
-
Silva, Jesús
Solano, Darwin
Fernández, Claudia
Nieto Ramos, Lainet
Urdanegui, Rosella
Herz, Jeannette
Mercado, Alberto
Ovallos-Gazabon, David
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7707
- Acceso en línea:
- https://hdl.handle.net/11323/7707
https://doi.org/10.1007/978-981-15-7234-0_88
https://repositorio.cuc.edu.co/
- Palabra clave:
- Data mining
Anomalous data
Algorithms
Automatic learning
Big data
Noise
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International